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<table width="100%"><tr><td>gamlss.mx-package(gamlss.mx)</td><td align="right">R Documentation</td></tr></table><object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e">
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<h2>The GAMLSS add on package for mixture distributions</h2>


<h3>Description</h3>

<p>
The main purpose of this package is to allow the user of the GAMLSS models to fit mixture distributions.
</p>


<h3>Details</h3>

<p>
<table summary="Rd table">
<tr>
  <td align="left">Package: </td>  <td align="left"> gamlss.mx</td>
</tr>
<tr>
  <td align="left"> Type: </td>  <td align="left"> Package</td>
</tr>
<tr>
  <td align="left"> Version: </td>  <td align="left"> 0.0</td>
</tr>
<tr>
  <td align="left"> Date: </td>  <td align="left"> 2005-08-3</td>
</tr>
<tr>
  <td align="left"> License: </td>  <td align="left"> GPL (version 2 or later) </td>
</tr>
</table>
<p>
This package has two main function the <code>gamlssMX()</code> which is loosly based on the
package <code>flexmix</code> of R and the function <code>gamlssNP()</code>  which is based on the <code>npmlreg</code> 
package of  Jochen Einbeck, Ross Darnell and John Hinde (2006) which in turns
is based on several GLIM4 macros originally written  by  Murray Aitkin and Brian 
Francis. It also contains the function 
<code>gqz()</code> which is written by  Nick Sofroniou and the function <code>gauss.quad()</code> 
written by Gordon Smyth.
</p>


<h3>Author(s)</h3>

<p>
Mikis Stasinopoulos &lt;<a href="mailto:d.stasinopoulos@londonmet.ac.uk">d.stasinopoulos@londonmet.ac.uk</a>&gt; and Bob Rigby &lt;<a href="mailto:r.rigby@londonmet.ac.uk">r.rigby@londonmet.ac.uk</a>&gt; 
</p>
<p>
Maintainer: Mikis Stasinopoulos &lt;d.stasinopoulos@londonmet.ac.uk&gt;
</p>


<h3>References</h3>

<p>
Jochen Einbeck, Ross Darnell and John Hinde (2006) npmlreg: Nonparametric maximum likelihood estimation for random effect
models, R package version 0.34
</p>
<p>
Rigby, R. A. and  Stasinopoulos D. M. (2005). Generalized additive models for location, scale and shape,(with discussion), 
<EM>Appl. Statist.</EM>, <B>54</B>, part 3, pp 507-554.
</p>
<p>
Stasinopoulos D. M., Rigby R.A. and Akantziliotou C. (2003) Instructions on how to use the GAMLSS package in R.
Accompanying documentation in the current GAMLSS  help files, (see also  <a href="http://www.gamlss.com/">http://www.gamlss.com/</a>).
</p>


<h3>See Also</h3>

<p>
<code><a onclick="findlink('gamlss', 'gamlss.html')" style="text-decoration: underline; color: blue; cursor: hand">gamlss</a></code>,<code><a onclick="findlink('gamlss', 'gamlss.family.html')" style="text-decoration: underline; color: blue; cursor: hand">gamlss.family</a></code>
</p>


<h3>Examples</h3>

<pre>
data(enzyme)
mmNO&lt;-gamlssMXfits(n=10,enzyme$act~1, family=NO, K=2)
mmNO
fyNO&lt;-dMX(y=seq(0,3,.01), mu=list(1.253, 0.1876), sigma=list(exp(-0.6665 ), exp(-2.573 )),
                  pi=list(0.4079609, 0.5920391 ), family=list("NO","NO") )
hist(enzyme$act,freq=FALSE,ylim=c(0,3.5),xlim=c(0,3),br=21)
lines(seq(0,3,.01),fyNO, col="red")
# equivalent model using gamlssNP
mmNP &lt;- gamlssNP(act~1, data=enzyme, random=~1,sigma.fo=~MASS,family=NO, K=2)
</pre>

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